Speaker Diarization Script
by pyannote · free · Last verified 2026-03-17
This script automates the process of creating turn-by-turn transcripts from multi-speaker audio files. It first uses the pyannote.audio library to perform speaker diarization, identifying who spoke and when. These speaker segments are then aligned and merged with a transcription generated by OpenAI's Whisper, producing a final text output that attributes each line of dialogue to a specific speaker.
https://github.com/pyannote/pyannote-audio ↗B
B—Above Average
Adoption: B+Quality: AFreshness: ACitations: BEngagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- Speaker diarization using pyannote.audio models, Transcription generation via OpenAI Whisper, Merging diarization and transcription data, Generation of time-stamped, speaker-labeled transcripts, Detection and labeling of overlapping speech segments, Speaker enrollment using audio samples for known speaker identification, Configuration of diarization parameters (e.g., min/max speakers), Processing of common audio formats (WAV, MP3, FLAC), Outputting transcripts in formats like TXT or JSON
- Integrations
- [object Object], [object Object], [object Object], [object Object]
- Use Cases
- [object Object], [object Object], [object Object], [object Object], [object Object]
- API Available
- No
- Language
- python
- Dependencies
- pyannote.audio, openai-whisper, torch, torchaudio, huggingface-hub
- Environment
- Python 3.10+, CUDA recommended
- Est. Runtime
- 5-15 minutes per hour of audio
- Tags
- speaker-diarization, audio-processing, transcription, pyannote-audio, openai-whisper, python-script, speech-to-text, multi-speaker-transcription, speaker-identification, command-line-tool, nlp-data-preparation
- Added
- 2026-03-17
- Completeness
- 0.85%
Index Score
60.4Adoption
72
Quality
83
Freshness
85
Citations
60
Engagement
0